Data Annotation Services

Enhance your AI and machine learning models with our expert annotation services. Our annotation services are a critical part of the development of artificial intelligence (AI) systems that are making the world safer, more efficient, and more enjoyable. We are committed to rapidly providing high-quality data that helps to train AI models that impart a positive impact on the world.

annotation

Why Choose Us?

Expertise

Our team of seasoned annotators has deep expertise in a variety of fields, including computer vision, natural language processing, and medical imaging. We can help ensure that your data is annotated accurately and with precision.

Efficiency

Our cloud-based platform can help you to accelerate the annotation process. The platform offers a variety of tools and features that can help to automate the annotation process, such as automatic object detection and segmentation.

Cost

We offer a diverse range of pricing options to fit the needs of businesses of all sizes. Businesses can choose to pay per annotation, per project, or on a subscription basis. This flexibility allows businesses to find a pricing option that aligns with their budget and requirements.

Types of Data Annotation Services

2D Bounding Boxes

A technique for accurately and efficiently annotating data. By drawing precise rectangular boxes around objects of interest in images or video frames, this method enables the identification and tracking of various objects, including vehicles, pedestrians, and animals. Widely used in computer vision and machine learning applications, 2D Bounding Box annotation is a crucial tool for training algorithms to recognize and classify objects in complex and dynamic real-world environments.

3D Cuboid Annotation

3D cuboid image annotation is a technique that can be used to detect and recognize 3D objects in images. By drawing a cuboid around an object in an image, machines can determine the depth of the object. This allows machines to more accurately and efficiently recognize objects in 3D space.

3D cuboid annotation is used in a variety of computer vision applications, including autonomous driving, robotics, medical imaging, and augmented reality. In autonomous driving, for example, 3D cuboid annotation can be used to identify and track other vehicles, pedestrians, and obstacles. In robotics, 3D cuboid annotation can be used to plan paths and avoid collisions. In medical imaging, 3D cuboid annotation can be used to identify and segment organs and tissues. And in augmented reality, 3D cuboid annotation can be used to overlay virtual objects onto the real world.

Key Point Annotation

Our highly skilled teams use key point annotation to meticulously trace the contours of objects and identify variations in shape by connecting individual points across them. This meticulous process enables the detection of intricate body features, including facial expressions and emotions, and is particularly useful in the field of facial recognition.

By leveraging the power of key point annotation, we are able to provide unparalleled accuracy and precision in our data annotation services. This technique enables the identification of even the most subtle nuances in facial expressions and body language, allowing for a more comprehensive understanding of human behavior and emotions.

Lines & Splines

The art of line and spline annotation is a powerful tool for visualizing data. By connecting two points on an image, these lines can depict a single value or trend in the data. Splines are similar to lines, but they are curved and can represent time-dependent changes in data.

In the hands of a skilled annotator, lines and splines can be used to create elegant and informative visualizations that can help viewers to better understand complex data, such as charts and graphs. They can also be used in medical imaging to identify areas of interest or anomalies.

Text Annotation

The technique of enriching textual data with layers of meaning, enabling deeper analysis and insights. This can encompass identifying named entities, categorizing text by sentiment, and tagging parts of speech.

It has various applications in literary studies, linguistics, and natural language processing. For example, it can identify literary devices, grammatical structures, and sentiment, and can train machine learning models to process written content. Though complex, the results of text annotation can be invaluable.

Polygons Annotation

Polygon annotation is method of image annotation that involves marking and drawing shapes on digital images. This technique enables the precise labeling of objects within images based on their position and orientation.

Polygon annotation is particularly for images with irregular dimensions, such as traffic and aerial images, which require precise annotations. Computer vision applications use polygon annotation to outline objects and areas of interest in an image, such as the boundaries of people and objects. This technique is essential for accurate object recognition and classification in computer vision.

Semantic Segmentation

The process of imbuing data with semantic information, empowering machines to better comprehend relationships between entities and concepts. This can encompass constructing knowledge graphs, developing ontologies, and mapping concepts.

The advanced technique facilitates the recognition, comprehension, and differentiation of objects within an image at the pixel level. By assigning each pixel to a specific class based on its location and the object’s boundaries, the technique enables accurate identification of objects in complex images.

This cutting-edge method finds extensive use in various fields, including autonomous navigation, medical imaging, and object detection. Its ability to precisely identify objects within images has made it an essential tool for advanced computer vision applications

3D Point Cloud Annotation

This is a sophisticated method of labeling and annotating 3D point clouds to enable comprehensive analysis and comprehension of image datasets. This technique is particularly useful for identifying and labeling 3D objects in space, such as buildings, vehicles, roads, trees, and other landmarks.

Advanced annotation techniques can be used to generate digital 3D models, which can be utilized for various applications such as 3D mapping, 3D visualization, and 3D modeling. Our image annotation services employ both automated algorithms and manual annotation to ensure the accuracy and timely delivery of 3D point cloud annotated datasets. This makes it a valuable tool for advanced computer vision applications.

Building a Better tomorrow with Data Annotation Services

Autonomous vehicles

We annotate images and videos of the road environment to help train machine learning models to recognize and respond to different scenarios on the road. This includes identifying objects such as pedestrians, vehicles, and traffic signs. Our data helps to make autonomous vehicles safer and more efficient.

Virtual advertising and product placement

By leveraging the power of 3D modeling, these services provide advertisers with highly accurate and detailed representations of their products and brands, which can be seamlessly integrated into virtual environments. This not only enhances the quality of advertising campaigns but also allows for the tracking and optimization of ad placements, based on data-driven insights from viewer behavior and eye movements.

Medical image analysis:

We annotate medical images such as X-rays, CT scans, and MRIs to help train machine learning models to detect abnormalities and assist medical professionals in diagnosing and treating patients. This includes identifying different structures such as organs, tumors, and blood vessels. Our data helps to improve the accuracy of medical diagnoses and treatments.

Natural language processing

We annotate text data to help train machine learning models to understand and generate human language. This includes identifying named entities, parts of speech, and sentiment. Our data helps to improve the accuracy of search engines, chatbots, and other natural language processing applications.

E-commerce product categorization

We annotate product images and descriptions to help train machine learning models to identify attributes such as color, size, and material. This data helps to improve product search and recommendation algorithms, and enhance the overall shopping experience for customers.

Social media content moderation

We annotate text, images, and videos to help train machine learning models to automatically detect and remove inappropriate or harmful content such as hate speech, violence, and nudity. This data helps to create a safer and more positive online environment for everyone.